M.H. Kalos and P.A. Whitlock. Monte Carlo Methods. Wiley, New York, 1986. Home/Search Document Not in Database Summary Related Articles Check |
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Stratified Sampling of 2-Manifolds - James Arvo State (2001) (Correct)
....from # by following a precise procedure. 1. 2 A Recipe for Sampling Algorithms Although there is a vast and mature literature an Monte Carlo methods, with many texts describing how to derive sampling algorithms for various geometries and density functions (see, for example, Kalos and Whitlock [6], Spanier and Gelbard [11] or Rubinstein [9] these treatments do not provide step by step instructions for deriving the types of algorithms that we frequently require in computer graphics. In this section we present a detailed recipe for how to convert an arbitrary parametrization # : 0, ....
M. H. Kalos and Paula A. Whitlock. Monte Carlo Methods, volume I, Basics. John Wiley & Sons, New York, 1986.
Negotiating Complex Contracts - Klein, Faratin, Sayama, al. (2002) (2 citations) (Correct)
....kinds of agents: hill climbers and annealers . The hill climbers use a very simple decision function: they accept a mutated contract only if its utility to them is greater than that of the last contract both agents accepted. Annealers are more complicated, implementing a Monte Carlo machine [5]. Each annealer haw a virtual temperature T, such that it will accept contracts worse than last accepted one with the probability: P(accept) max(1, e DU T ) where DU is the utility change between the contracts. In other words, the higher the virtual temperature, and the smaller the ....
Kalos, M.H. and P.A. Whitlock, Monte Carlo methods. 1986, New York: J. Wiley & Sons.
Stochastic Conformational Roadmaps for Computing.. - Apaydin, Brutlag, .. (2004) (1 citation) (Correct)
....disease. Despite its importance, the protein folding process remains a mystery. While it is traditionally studied through tedious and costly laboratory experiments, computer simulation plays an increasingly important role. Classic techniques for simulating molecular motion, including Monte Carlo [15] and molecular dynamics [12] methods, have two major drawbacks: 1. They compute individual pathways, one at a time; however, many interesting properties of molecular motion, in particular, the ensemble properties, are best characterized statistically over many pathways. For instance, the new ....
M.H. Kalos and P.A. Whitlock. Monte Carlo Methods, volume 1. John Wiley & Son, New York, 1986.
Efficient Importance Sampling Techniques for the Photon Map - Keller, Wald (2000) (Correct)
....and increased rendering efficiency. Our importance driven generation of the photon map controls the deposition, which is more efficient than controlling the scatter Note that the composition method can raise variance. Thus it is more efficient to use biased post stratification estimators [KW86] ing directions. It also allows to automatically generate the complete caustic photon map at the required high resolution. Finally we presented an efficient sampling scheme for environments with a large number of light sources of which a fraction is permanently occluded. These importance ....
M. Kalos and P. Whitlock. Monte Carlo Methods, Volume I: Basics. J. Wiley & Sons, 1986. 3
Randomized Kinodynamic Motion Planning with Moving Obstacles - Hsu, Kindel, Latombe, Rock (2000) (22 citations) (Correct)
....when the space becomes less expansive. 4.4 Approximating IDEAL SAMPLE The above analysis assumes the use of IDEAL SAMPLE, which picks a new milestone uniformly at random from the reachability set of the existing milestones. One way to implement IDEAL SAMPLE would be rejection sampling [KW86] which throws away a fraction of samples in regions that are more densely sampled than others. However, rejection sampling is not efficient: many potential candidates are thrown away in order to achieve the uniform distribution. So instead, our implemented planners try to approximate the ideal ....
M.H. Kalos and P.A. Whitlock. Monte Carlo Methods, volume 1. John Wiley & Son, New York, 1986.
Quasi-Randomized Path Planning - Michael Branicky Steven (2001) (4 citations) (Correct)
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M.H. Kalos and P.A. Whitlock. Monte Carlo Methods. Wiley, New York, 1986.
A Bayesian Framework For Considering Probability Distributions - Of Image Segments (Correct)
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M. H. Kalos and P. A. Whitlock, Monte Carlo Methods. New York, NY: Wiley, 1986.
Methods for Numerical Integration of High-Dimensional.. - With Application To (Correct)
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M. H. Kalos and P. A. Whitlock. Monte Carlo Methods. Wiley, New York, NY, 1986.
Methods for Numerical Integration of High-Dimensional.. - Application To.. (Correct)
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M. H. Kalos and P. A. Whitlock. Monte Carlo Methods. Wiley, New York, NY, 1986.
Workspace Importance Sampling for Probabilistic Roadmap.. - Hanna Kurniawati David (2004) (Correct)
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Kalos, M.H., P.A. Whitlock. Monte Carlo Methods. John Wiley & Sons, New York, 1986.
Building Inferentially Tractable Models of Complex Social Systems: .. - Butts (2005) (Correct)
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Kalos, M. H. and Whitlock, P. A. (1986). Monte Carlo Methods, Volume I: Basics. John Wiley and Sons, New York.
Polarizable Force Fields For Flexible Molecules - Holt (2004) (Correct)
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M.H. Kalos and P.A. Whitlock. Monte Carlo Methods, Volum I: Basics. John Wiley & Sons, Inc., 1986.
Planning Algorithms - LaValle (2004) (3 citations) (Correct)
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M. H. Kalos and P. A. Whitlock. Monte Carlo Methods. Wiley, New York, NY, 1986.
Weighted Importance Sampling Techniques for Monte Carlo.. - Bekaert, Sbert, Willems (2000) (1 citation) (Correct)
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M. H. Kalos and P. Whitlock. The Monte Carlo method. J. Wiley and sons, 1986.
User's Manual for Environmental programs - Mech, Prusinkiewicz (1998) (Correct)
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KALOS,M.H.,AND WHITLOCK,P.A.Monte Carlo Methods. John Wiley & Sons, New York, 1986.
Efficient Rendering of Local Subsurface Scattering - Mertens, Kautz, Bekaert.. (Correct)
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M. H. Kalos and P. A. Whitlock. Monte Carlo Methods, Volume 1: Basics. Wiley, 1986.
Systematic Integration of Parameterized Local.. - Bambha.. (2004) (Correct)
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M. Kalos and P. Whitlock, Monte Carlo Methods. New York: Wiley, 1986.
State of the Art in Monte Carlo Ray Tracing for Realistic Image.. - Jensen (2001) (Correct)
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M. H. Kalos and Paula A. Whitlock. Monte Carlo Methods, volume I, Basics. John Wiley & Sons, New York, 1986.
An Information-Theory Framework for the Study of the Complexity.. - Feixas (2002) (Correct)
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M. H. Kalos and P. A. Whitlock. The Monte Carlo Method. John Wiley & Sons, 1986.
Monte Carlo Simulation of the Electrodeposition of Copper - Additive-Free Acidic Sulfate (2002) (Correct)
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M. H. Kalos and P. A. Witlock, Monte Carlo Methods. Part I: Theory, John Wiley & Sons, New York #1986#.
Stochastic Roadmap Simulation: An Efficient Representation and - Algorithm For Analyzing (Correct)
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M.H. Kalos and P.A. Whitlock. Monte Carlo Methods, volume 1. John Wiley & Son, New York, 1986.
The use of global random directions to compute radiosity. Global .. - Casasayas (1996) (6 citations) (Correct)
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Malvin H. Kalos and Paula A. Withlock. Monte Carlo Methods,Volume I. John Wiley & Sons, New York, 1984.
Atomic Motion in Magneto-Optical Double-Well Potentials: - New Testing Ground (2001) (Correct)
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M. H. Kalos and P. A. Whitlock, Monte Carlo Methods (John Wiley & Sons Inc., New York, 1986), Vol. 1, p.73. 27
Subspace Linear Discriminant Analysis for Face Recognition - Zhao, Chellappa, Phillips (1999) (7 citations) (Correct)
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M.H. Kalos and P.A. Whitlock, Monte Carlo Methods, New York: Wiley, 1986.
Efficient Multidimensional Sampling - Kollig, Keller (2002) (2 citations) (Correct)
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M. Kalos and P. Whitlock. Monte Carlo Methods, Volume I: Basics. J. Wiley & Sons, 1986. 2
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